Работы, цитирующие эту работу

Работ: 5

Работа: The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions

1. Meta-XPFL: An Explainable and Personalized Federated Meta-Learning Framework for Privacy-Aware IoMT

   Mohamed Adel Serhani, Asadullah Tariq, Tariq Qayyum +3

   СтатьяPrivacy-Preserving Technologies in DataIEEE Internet of Things Journal2025Цитирований: 1

   ABIABI:AkademIndex/openalex/2026.other.131081

2. Dermatologist-Level Classification of Skin Cancer Using Cascaded Ensembling of Convolutional Neural Network and Handcrafted Features Based Deep Neural Network

   Akhilesh Sharma, Shamik Tiwari, Gaurav Aggarwal +7

   СтатьяCutaneous Melanoma Detection and ManagementIEEE Access2022Цитирований: 0

   ABIABI:AkademIndex/openalex/2022.article.000015

3. TV-SAM: Increasing Zero-Shot Segmentation Performance on Multimodal Medical Images Using GPT-4 Generated Descriptive Prompts Without Human Annotation

   Zekun Jiang, Dongjie Cheng, Ziyuan Qin +10

   СтатьяDomain Adaptation and Few-Shot LearningBig Data Mining and Analytics2024Цитирований: 0

   ABIABI:AkademIndex/openalex/2024.article.000199

4. Enhancing medical image segmentation with adaptive convolution and dynamic high-frequency feature enhancement

   Wenguang Xu, Qian Dong, Shiren Li +5

   СтатьяAI in cancer detectionThe Visual Computer2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.016820

5. An Optimal Deep Hybrid Framework with Selective Kernel U-Net for Skin Lesion Detection and Classification

   Guzal Gulmirzaeva, Róbert Hudec, Baxtiyorjon Akbaraliev +1

   СтатьяCutaneous Melanoma Detection and ManagementBioengineering2026Цитирований: 0

   ABIABI:AkademIndex/openalex/2026.article.010692